How to Serve 3 Million ML Models at Scale: The Architecture Patterns That Actually Work (2026)
Scaling ML model serving to millions of models demands metadata-binary separation, pre-computed search tokens, read-routed replica sets, and two-layer autoscaling. Here is the architecture that works.
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